Detecting media watermarks in magnetic field data

ABSTRACT

Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to detect media watermarks in magnetic field data are disclosed herein. Example media monitors disclosed herein include a magnetic field estimator to determine first magnetic field data, the magnetic field estimator in communication with a magnetometer. Disclosed example media monitors also include a correlator to correlate the first magnitude field data with a reference sequence to determine second magnetic field data. Disclosed example media monitors further include a watermark decoder to process the second magnetic field data to detect an audio watermark encoded in an audio signal.

RELATED APPLICATION(S)

This patent arises from a continuation of U.S. patent application Ser.No. 17/011,769 (now U.S. Pat. No. ______), which is titled “DETECTINGMEDIA WATERMARKS IN MAGNETIC FIELD DATA,” and which was filed on Sep. 3,2020, which is a continuation of U.S. patent application Ser. No.16/417,131 (now U.S. Pat. No. 10,769,206), which is titled “DETECTINGMEDIA WATERMARKS IN MAGNETIC FIELD DATA,” and which was filed on May 20,2019, which is a continuation of U.S. patent application Ser. No.15/608,675 (now U.S. Pat. No. 10,318,580), which is titled “DETECTINGMEDIA WATERMARKS IN MAGNETIC FIELD DATA,” and which was filed on May 30,2017, which is a continuation of U.S. patent application Ser. No.14/133,069 (now U.S. Pat. No. 9,679,053), which is titled “DETECTINGMEDIA WATERMARKS IN MAGNETIC FIELD DATA,” and which was filed on Dec.18, 2013, which claims the benefit of U.S. Provisional Application Ser.No. 61/825,495, which is titled “AUDIO WATERMARK DETECTION WITHSMARTPHONE” and which was filed on May 20, 2013. U.S. ProvisionalApplication Ser. No. 61/825,495, U.S. patent application Ser. No.14/133,069, U.S. patent application Ser. No. 15/608,675, and U.S. patentapplication Ser. No. 16/417,131 are hereby incorporated by reference intheir respective entireties. Priority to U.S. Provisional ApplicationSer. No. 61/825,495, U.S. patent application Ser. No. 14/133,069, U.S.patent application Ser. No. 15/608,675, and U.S. patent application Ser.No. 16/417,131 is hereby claimed.

FIELD OF THE DISCLOSURE

This disclosure relates generally to media watermarking and, moreparticularly, to detecting media watermarks in magnetic field data.

BACKGROUND

Watermarks can be embedded or otherwise included in media data and/orsignals to enable additional information to be conveyed with the media.For example, audio watermarks can be embedded or otherwise included inthe audio data/signal portion of a media stream, file and/or signal toconvey data, such as media identification information, copyrightprotection information, etc., with the media. Such watermarks enablemonitoring of the distribution and/or use of media, such as by detectingwatermarks present in television broadcasts, radio broadcasts, streamedmultimedia content, etc., to identify the particular media beingpresented to viewers, listeners, users, etc. Such information can bevaluable to advertisers, content providers, and the like.

Magnetometers and other magnetic field measurement sensors have becomecommon components included in modern portable electronic devices, suchas smartphones, handset devices, tablet computers, etc. Typically, amagnetometer or similar sensing component is included in a portabledevice to provide magnetic field data representative of measured valuesof a magnetic field in the vicinity of the portable device. The portabledevice can then use this magnetic field data to determine a spatialorientation of the portable device. In at least some examples, othersoftware applications executing on the portable device and/oraccessories capable of interfacing with the portable device can gainaccess to this magnetic field data as well.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example media monitoring systemincluding an example portable device having an example media devicemonitor capable of detecting media watermarks in magnetic field data andpositioned to detect watermarks in media presented by an example mediadevice having a first configuration.

FIG. 2 is a block diagram of the example media monitoring system of FIG.1 but with the example portable device positioned to detect watermarksin media presented by an example media device having a secondconfiguration.

FIG. 3 is a block diagram of an example implementation of the mediadevice monitor of FIGS. 1 and/or 2 .

FIG. 4 is a block diagram of a first example watermark detector that maybe used to implement the example media device monitor of FIGS. 1, 2and/or 3 .

FIG. 5 is a block diagram of a second example watermark detector thatmay be used to implement the example media device monitor of FIGS. 1, 2and/or 3 .

FIG. 6 is a flowchart representative of example machine readableinstructions that may be executed to implement the example media devicemonitor of FIGS. 1, 2 and/or 3 .

FIG. 7 a flowchart representative of example machine readableinstructions that may be used to implement at least a portion of theexample machine readable instructions of FIG. 6 and/or that may beexecuted to implement the first example watermark detector of FIG. 4 .

FIG. 8 a flowchart representative of example machine readableinstructions that may be used to implement at least a portion of theexample machine readable instructions of FIG. 6 and/or that may beexecuted to implement the second example watermark detector of FIG. 5 .

FIGS. 9-10 illustrated example operational results for the example mediadevice monitor of FIGS. 1, 2 and/or 3 .

FIG. 11 is a block diagram of an example processor platform that mayexecute the example machine readable instructions of FIGS. 6, 7 and/or 8to implement the example media device monitor of FIGS. 1, 2 and/or 3 ,the first example watermark detector of FIG. 4 , the second examplewatermark detector of FIG. 5 , and/or the example portable device ofFIGS. 1 and/or 2 .

Wherever possible, the same reference numbers will be used throughoutthe drawing(s) and accompanying written description to refer to the sameor like parts, elements, etc.

DETAILED DESCRIPTION

Methods, apparatus, systems and articles of manufacture (e.g., physicalstorage media) to detect media watermarks in magnetic field data aredisclosed herein. Example methods disclosed herein to detect mediawatermarks can include accessing multidimensional magnetic field datarepresentative of values of a magnetic field measured within a firstdistance of audio circuitry that is to output an audio signalcorresponding to media presented by a media device. Such example methodscan also include processing the multidimensional magnetic field data todetect a watermark included in the audio signal. For example, the audiocircuitry can include speaker leads electrically coupling a speaker to aspeaker driver circuit, and processing the multidimensional magneticfield data can include detecting variations in the magnetic field thatare induced by an electrical signal being carried by the speaker leadsto cause the speaker to output the audio signal.

In some such example methods, accessing the multidimensional magneticfield data can include obtaining the multidimensional magnetic fielddata from an interface providing access to a magnetometer of a portabledevice. Additionally or alternatively, in some examples, themultidimensional magnetic field data can include a plurality ofdirectional components. In some such example methods, processing themultidimensional magnetic field data can include (1) processing thedirectional components to determine magnitude values representative of amagnitude of the magnetic field over time, and (2) processing themagnitude values to detect the watermark included in the audio signal.

For example, processing the magnitude values can include (1)transforming the magnitude values into a frequency domain to determinetransformed magnetic field data, and (2) processing the transformedmagnetic field data to detect the watermark. In some such examples, thewatermark modulates a first frequency of the audio signal, themultidimensional magnetic field data is accessed at a first samplingrate less than twice the first frequency, and processing the transformedmagnetic field data includes evaluating the transformed magnetic fielddata at a second frequency, different from the first frequency, todetect the watermark. In such examples, the second frequency is selectedto compensate for aliasing caused by accessing the multidimensionalmagnetic field data at the first sampling rate. Additionally oralternatively, in some such examples, the audio circuitry drives aspeaker that is to emit the audio signal, the watermark is included in afirst frequency range of the audio signal that is below a threshold offrequencies capable of being emitted by the speaker, and processing thetransformed magnetic field data includes evaluating a portion of thetransformed magnetic field data corresponding to the first frequencyrange to detect the watermark.

In other examples, the multidimensional magnetic field data is firstmagnetic field data, and processing the magnitude values includes (1)correlating the magnitude values with a reference sequence to determinesecond magnetic field data, and (2) processing the second magnetic fielddata to detect the watermark.

These and other example methods, apparatus, systems and articles ofmanufacture (e.g., physical storage media) to detect media watermarks inmagnetic field data are disclosed in further detail below.

Example methods, apparatus, systems and articles of manufacture (e.g.,physical storage media) to detect media watermarks in magnetic fielddata as disclosed herein enable detection of an informational signal,such a watermark, which is embedded or otherwise included in a hostaudio signal to be emitted by one or more speaker(s), using anorientation sensor, such as a magnetometer or other magnetic sensor,included in a metering device. For example, such metering devices can beimplemented by smartphones, handset devices, tablet computers, etc.,because orientation sensors, such as magnetometers, are often present inthose types of consumer devices. In other examples, dedicated platformscontaining one or more orientation sensors, such as magnetometers, canbe used to implement metering devices capable of detecting mediawatermarks in magnetic field data as disclosed herein.

Detecting media watermarks in magnetic field data, as disclosed herein,can provide benefits over prior watermark detection techniques. Forexample, because magnetic field data is used to detect one or morewatermark(s) embedded in an audio signal, the example methods,apparatus, systems and articles of manufacture (e.g., physical storagemedia) disclosed herein do not require direct or even indirect access tothe audio signal containing the watermark. This can be especiallybeneficial when monitoring media being presented by a media device thatprevents (e.g., via digital rights management techniques) externalaccess to the media data being presented by the media device.

Furthermore, watermark detection using magnetic field data, as disclosedherein, permits detection of watermark data embedded in an audio signalat frequencies below a frequency threshold supported by the speaker(s)of the media device. For example, due to the physical characteristics ofthe diaphragms in the speaker(s) of the media device, the speaker(s) mayhave a frequency response range bounded by a lower limit or thresholdsuch that audio frequencies below that threshold are unable to berendered by the speaker(s). If a watermark is embedded in a frequencyrange below such a threshold, prior watermark detection techniques thatrely on processing audio data collected via a microphone will be unableto detect the watermark in the audio emitted from the speaker(s).However, such a watermark may still cause magnetic field variations whenthe audio signal is applied as an electrical current to the speakerleads and/or other audio circuitry driving the speaker(s). Accordingly,watermark detection using magnetic field data, as disclosed herein, maybe able to detect watermarks in scenarios where prior watermarkdetection techniques based on processing sensed audio data would fail.

Turning to the figures, a block diagram of an example media monitoringsystem 100 employing detection of media watermarks in magnetic fielddata as disclosed herein is illustrated in FIG. 1 . The example mediamonitoring system 100 supports monitoring of media presented at one ormore monitored sites, such as an example monitored site 105 illustratedin FIG. 1 . The monitored site 105 includes an example media device 110,which is also referred to herein as a media presentation device 110.Although the example of FIG. 1 illustrates one monitored site 105 andone media device 110, media monitoring based on detection of mediawatermarks in magnetic field data as disclosed herein can be used inmedia monitoring systems 100 supporting any number of monitored sites105 having any number of media devices 110.

The media monitoring system 100 of the illustrated example includes anexample media device meter 125, also referred to as a meter 125, a sitemeter 125, a site unit 125, a home unit 125, a portable device 125,etc., to monitor media presented by the media device 110. In theillustrated example, the media monitored by the media device meter 125can correspond to any type of media presentable by the media device 110.For example, monitored media can correspond to media content, such atelevision programs, radio programs, movies, etc., as well ascommercials, advertisements, etc. In the illustrated example, the mediadevice meter 125 determines metering data that may identify and/or beused to identify media presented by the media device (and, thus, infermedia exposure) at the monitored site 105. The media device meter 125then stores and reports this metering data via an example network 135 toan example data processing facility 140. The data processing facility140 performs any appropriate post-processing of the metering data to,for example, determine audience ratings information, identify targetedadvertising to be provided to the monitored site 105, etc. In theillustrated example, the network 135 can correspond to any type(s)and/or number of wired and/or wireless data networks, or any combinationthereof.

In the illustrated example, the media device 110 monitored by the mediadevice meter 125 can correspond to any type of audio, video and/ormultimedia presentation device capable of presenting media audiblyand/or visually. For example, the media device 110 can correspond to atelevision and/or display device that supports the National TelevisionStandards Committee (NTSC) standard, the Phase Alternating Line (PAL)standard, the Systeme Electronique pour Couleur avec Mémoire (SECAM)standard, a standard developed by the Advanced Television SystemsCommittee (ATSC), such as high definition television (HDTV), a standarddeveloped by the Digital Video Broadcasting (DVB) Project, etc. As otherexamples, the media device 110 can correspond to a multimedia computersystem, a personal digital assistant, a cellular/mobile smartphone, aradio, a tablet computer, etc.

In the media monitoring system 100 of the illustrated example, the mediadevice meter 125 and the data processing facility 140 cooperate toperform media monitoring based on detecting media watermarks. Moreover,the media device meter 125 is able to detect media watermarks inmagnetic field data as disclosed herein. Examples of watermarks includeidentification codes, ancillary codes, etc., that may be transmittedwithin media signals. For example, identification codes can betransmitted as watermarked data embedded or otherwise included withmedia (e.g., inserted into the audio, video, or metadata stream ofmedia) to uniquely identify broadcasters and/or media (e.g., content oradvertisements). Watermarks can additionally or alternatively be used tocarry other types of data, such as copyright protection information,secondary data (e.g., such as one or more hyperlinks pointing tosecondary media retrievable via the Internet and associated with theprimary media carrying the watermark), commands to control one or moredevices, etc. Watermarks are typically extracted using a decodingoperation.

In contrast, signatures are a representation of some characteristic ofthe media signal (e.g., a characteristic of the frequency spectrum ofthe signal). Signatures can be thought of as fingerprints. They aretypically not dependent upon insertion of data in the media, but insteadpreferably reflect an inherent characteristic of the media and/or thesignal transporting the media. Systems to utilize codes and/orsignatures for audience measurement are long known. See, for example,U.S. Pat. No. 5,481,294 to Thomas et al., which is hereby incorporatedby reference in its entirety.

In the illustrated example of FIG. 1 , the media device meter 125 isimplemented by a portable device 125 including an example magnetometer145 or any other type(s) and/or number of orientation sensor(s) 145(e.g., such as one or more magnetic sensors, electronic compasses, etc.)capable of measuring a magnetic field in the vicinity of the portabledevice 125. As such, the portable device 125 can correspond to any typeof portable device having magnetic field sensing capabilities, such as,but not limited to, a smartphone, a tablet computer, a handheld device,etc. In some examples, the media device meter 125 can be implemented bya metering device intended to be relatively stationary, but includingthe example magnetometer 145 or other orientation sensor(s) 145.Furthermore, in some examples, the media device meter 125 can beimplemented by or otherwise included in the media device 110, such aswhen the media device 110 corresponds to a portable device (e.g., asmartphone, a tablet computer, a handheld device, etc.) capable ofpresenting media and also including the example magnetometer 145 orother orientation sensor(s) 145. (This latter implementation can beespecially useful in example scenarios in which a media monitoringapplication is executed on the media device 110 itself, but the mediadevice 110 prevents, e.g., via digital rights management or othertechniques, third-party applications, such as the media monitoringapplication, from accessing protected media data stored on the mediadevice 110.) For convenience, and without loss of generality, the termmagnetometer is used herein to refer to any type of magnetic fieldsensing element (e.g., such as a magnetic sensor, an orientation sensor,an electronic compass, etc.).

Magnetometers, such as the example magnetometer 145 of FIG. 1 , areoften included as components in modern portable devices (e.g.,smartphones, handset devices, tablet computers, etc.), such as theportable device 125. A magnetometer, such as the magnetometer 145, is adevice that provides magnetic field vector measurements or, moregenerally, multidimensional magnetic field data representative of amagnetic field in the vicinity of the magnetometer (and, by extension,in the vicinity of the device including the magnetometer). In someexamples, the magnetic field data obtained from the magnetometer 145 ismultidimensional magnetic field data that includes multiple directionalcomponents representative of the strength and/or some other value of themagnetic field in multiple directions, such as two (2) orthogonaldirections referred to herein as the x and y directions, three (3)orthogonal directions referred to herein as the x, y and z directions,etc. Typically, the portable device includes functionality to processthe magnetic field data provided by the magnetometer to determine thespatial orientation of the portable device. For example, softwaredevelopment kits (SDKs) for Apple® iOS®, Android™, Windows®, andBlackberry® smartphones include application interfaces (APIs) defined toenable applications executing on the smartphones to access themagnetometer and obtain the magnetic field data representative of thevalues of, for example, the x, y and z directional components of themagnetic field in the vicinity of the smartphone. Typical priorapplications then process the obtained magnetic field data to determinean orientation of the smartphone.

In addition or as an alternative to including functionality capable ofdetermining device orientation from magnetic field data obtained fromthe magnetometer 145, the portable device 125 of the illustrated examplealso includes an example media device monitor 150 to detect watermark(s)in the magnetic field data obtained from the magnetometer 145. Forexample, a watermark that is detectable in the magnetic field data mayoriginate from an audio signal that is to be emitted by examplespeaker(s) 155 of the media device 110. In such examples, the mediadevice 110 may generate a varying electrical current corresponding tothe audio signal in audio circuitry (e.g., speaker leads and a speakerdriver circuit) driving the speaker(s) 155. This varying electriccurrent can induces a varying magnetic field in the audio circuitry(e.g., speaker leads and a speaker driver circuit), which may be sensedby the magnetometer 145 when the portable device 125 placed within afirst distance (e.g., adjacent to or within a few inches, feet or someother distance) of the speaker(s) 155 of the media device 110. In someexamples, the media device monitor 150 detects the watermark(s) includedin the audio signal to be emitted by example speaker(s) 155 by detectingvariations caused by the watermark(s) in the magnetic field dataobtained from the magnetometer 145. An example implementation of themedia device monitor 150 is illustrated in FIG. 3 , which is describedin further detail below.

In the illustrated example of FIG. 1 , the portable device 125, which isto monitor media presented by the media device 110, is positioned withina first distance (e.g., adjacent to or within a few inches, feet or someother distance) of the media device 110 to be able to sense magneticfield variations induced by the audio circuitry driving the speaker(s)155 of the media device. However, in some examples, the speaker(s) 155are positioned away from the media device 110, such as when thespeaker(s) 155 correspond to any type(s) and/or number of wirelessspeaker(s) 155. Accordingly, FIG. 2 illustrates a second exampleconfiguration of the media monitoring system 100 in which the portabledevice 125 is positioned within a first distance (e.g., adjacent to orwithin a few inches, feet or some other distance) of the examplespeaker(s) 155 (which are wireless speaker(s) in the illustratedexample) but a farther distance away from the media device 110, to beable to sense magnetic field variations induced by the audio circuitryin the speaker(s) 155.

In some examples, to aid in the proper positioning of the portabledevice 125, the media device monitor 150 causes the portable device 125to indicate whether the portable device 125 has been positioned withinthe first distance of the media device 110 and/or the speakers 155 andis able to detect watermarks using magnetic field data. For example, themedia device monitor 150 may cause an output indicator, such as a light,a tone, a symbol on a display of the portable device 125, etc., to beasserted when the media device monitor 150 determines that validwatermarks are being detected (e.g., based on cyclical redundancy check(CRC) bits or other validation data included in the detected watermark).Outputting such an indicator can provide feedback to an operator of theportable device 125, which notifies the operator when the portabledevice 125 has been placed within a first distance of the media device110 and/or the speakers 155 suitable for accurately detectingwatermarks.

An example implementation of the media device monitor 150 of FIGS. 1and/or 2 , which may be included in or otherwise implemented by themedia device meter 125 (e.g., which may be a portable device 125), isillustrated in FIG. 3 . The example media device monitor 150 of FIG. 3includes an example magnetic field estimator 305 to estimate values of amagnetic field in the vicinity of the media device meter 125 usingmagnetic field data obtained from the example magnetometer 145. In someexamples, the magnetic field estimator 305 accesses magnetic field datadetermined by the magnetometer 145 using one or more APIs, as describedabove. For example, the media device meter 125 (e.g., which may be aportable device 125) may provide an API or other function call forreading the magnetic field data returned by the magnetometer 145 at agiven sampling rate, such as a sampling rate of 40 Hz or some otherrate. The sampling rate for obtaining magnetic field data is determinedby, for example, the time involved in measuring the magnetic field withthe magnetometer 145 (e.g., which may be approximately 15 ms. or someother interval of time). In some examples, the sampling rate forobtaining magnetic field data is additionally or alternativelydetermined by an automatic power-down period configured to occur aftereach magnetic field measurement performed by the magnetometer 145. Thesampling rate for obtaining magnetic field data can also be limited byother latencies in the operating system (OS) of the media device meter125 (which may be a portable device 125). For example, the samplinginterval (Ts) and, thus, the sampling rate (Fs=1/Ts) for obtainingmagnetic data may be equal to the sum of one or more of the foregoingtime intervals, such as given by the expression in Equation 1, which is:

$\begin{matrix}{{Fs} = {\frac{1}{Ts} = \frac{1}{T_{measurement} + T_{{power} - {down}} + T_{latencies}}}} & {{Equation}1}\end{matrix}$

where T_(measurement) represents the magnetic field measurementinterval, T_(power-down) represents the power down interval, andT_(latencies) represents the latency interval.

Although possible sampling rates may increase in the future due toimprovements in sensor technology and device drivers (e.g., which mayallow for higher bandwidth communications), even fairly low samplingrates for obtaining magnetic field data from the magnetometer 145 canpermit data communication at multiple bits per second, depending onsignal modulation scheme, signal level, ambient noise level, etc. Forexample, noise in the magnetic field values returned by the magnetometer145 can be caused by the Earth's magnetic field, other electronicequipment in the vicinity of the media device meter 125, motion of themedia device meter 125, etc. For example, the magnetic field valuesreturned by the magnetometer 145 can be a function of multiplecomponents, such as given by the expression in Equation 2, which is:

M_(measured) =M _(audio circuit) +M _(Earth) +M _(other)   Equation 2

where M_(audio circuit) represents the magnetic field induced by theaudio circuitry of the media device 110 (and which may contain thewatermark(s) to be detected), M_(Earth) represents the magnetic field ofthe Earth, and M_(other) represents magnetic field(s) induced by otherelectronic equipment in the area, as well as any other sources ofmagnetic field distortions, noise, etc.

In the illustrated example of FIG. 3 , the magnetic field estimator 305accesses magnetic field data from the magnetometer 145 at a samplingrate Fs to form a sequence of magnetic field data representative ofvalues of a magnetic field measured over time and, presumably, within afirst distance of audio circuitry that is to output an audio signalcontaining one or more audio watermarks to be detected. In someexamples, the magnetic field data obtained by the magnetic fieldestimator 305 contains multiple directional components representative ofthe strength and/or some other measurement quantity of the magneticfield in multiple directions, such as the orthogonal x, y and/or zdirectional components mentioned above. In some such examples, themagnetic field estimator 305 processes the directional components todetermine magnitude values representative of a magnitude of the magneticfield over time. For example, if the magnetic field data contains twodirectional components, the magnetic field estimator 305 can determinethe determine magnitude values for the magnetic field according toEquation 3, which is:

|{right arrow over (B(t))}|=√{square root over (B_(x) ²(t)+B _(y)²(t))}  Equation 3

In Equation 3, |{right arrow over (B(t))}| represents the magnitudevalue of the magnetic field vector {right arrow over (B(t))}=(B_(x)(t),B_(y)(t)) at sample time t, Mt) represents the x-directional magneticfield component at sample time t, and B_(y)(t) represents they-directional magnetic field component at sample time t. As anotherexample, if the magnetic field data contains three directionalcomponents, the magnetic field estimator 305 can determine the determinemagnitude values for the magnetic field according to Equation 4, whichis:

|{right arrow over (B(t))}|=√{square root over (B_(x) ²(t)+B _(y) ²(t)+B_(z) ²(t))}  Equation 4

In Equation 4, |{right arrow over (B(t))}| represents the magnitudevalue for the magnetic field vector {right arrow over (B(t))}=(B_(x)(t),B_(y)(t), B_(z)(t)) at sample time t, B_(x)(t) represents thex-directional magnetic field component at sample time t, B_(y)(t)represents the y-directional magnetic field component at sample time t,and B_(z)(t) represents the z-directional magnetic field component atsample time t.

The example media device monitor 150 of FIG. 3 also includes an examplewatermark detector 310 to process the magnetic field data obtained bythe magnetic field estimator 305 detect one or more watermarks included(e.g., induced) in the magnetic field data by an audio signalcorresponding to media presented by a media device, such as the mediadevice 110. For example, if the magnetic field estimator 305 determinesmagnitude values of the magnetic field data, then the watermark detector310 may process the magnitude values of the magnetic field data todetect one or more watermarks included in the audio signal and furtherincluded in the magnetic field data due to magnetic field variationscaused by audio circuitry providing the audio signal to the speaker(s)155 of the media device 110. The particular type(s) of watermarkdetection algorithm(s) implemented by the watermark detector 310 willdepend on the type(s) of watermark encoding algorithm(s) used to embedor otherwise include the audio watermark(s) in the audio signal. Twoexample implementations of the watermark detector 310, which correspondto two different families of watermark encoding algorithm(s), areillustrated in FIGS. 4 and 5 , which are described in further detailbelow.

A first example implementation of the watermark detector 310 of FIG. 3is illustrated in FIG. 4 . The first example implementation is tailoredto detect watermarks encoded in one or more frequencies of an audiosignal, or otherwise encoded in the frequency domain of the audiosignal. Examples of watermarks encoded in the frequency domain of anaudio signal and that can be detected using the example watermarkdetector 310 of FIG. 3 include, but are not limited to, examplesdescribed in U.S. Pat. No. 8,359,205, entitled “Methods and Apparatus toPerform Audio Watermarking and Watermark Detection and Extraction,”which issued on Jan. 22, 2013, U.S. Pat. No. 8,369,972, entitled“Methods and Apparatus to Perform Audio Watermarking Detection andExtraction,” which issued on Feb. 5, 2013, and U.S. Publication No.2010/0223062, entitled “Methods and Apparatus to Perform AudioWatermarking and Watermark Detection and Extraction,” which waspublished on Sep. 2, 2010, all of which are hereby incorporated byreference in their entireties. U.S. Pat. No. 8,359,205, U.S. Pat. No.8,369,972 and U.S. Publication No. 2010/0223062 describe examplewatermarking systems in which a watermark is included in an audio signalby manipulating a set of frequencies of the audio signal.

Turning to FIG. 4 , the example watermark detector 310 illustratedtherein includes an example frequency transformer 405 to transformmagnetic field data, such a magnitude values determined by the magnitudefield estimator 305 and representative of a magnitude of a magneticfield over time, into a frequency domain to determine transformedmagnetic field data. For example, the frequency transformer 405 canperform any transform operation on input magnetic field data (e.g., theinput magnetic field magnitude value), such as a fast Fourier transform(FFT), a discrete Fourier transform (DFT), a discrete cosine transform(DCT), a Hadamard transform, etc., to determine the transformed magneticfield data, which represents values of the magnetic field in a frequencydomain (or other transform domain, such as a wavelet domain, etc.).

The example watermark detector 310 of FIG. 4 also includes an examplewatermark decoder 410 to detect a watermark in the transformed magneticfield data determined by the frequency transformer 405. The watermarkdetection/decoding algorithm(s) implemented by the watermark decoder 410depends on the type of encoding algorithm(s) used to encode thewatermark in the audio signal. For example, the watermark decoder 410may be configured to evaluate transformed magnetic field data at one ormore frequencies and/or in one or more ranges of frequencies to detect awatermark that was included in an audio signal. For example, thewatermark may be encoded in a first range of frequencies of an audiosignal such that the watermark is inaudible in the watermarked audiosignal. In such examples, when media device 110 applies the watermarkedaudio signal to the audio circuitry driving the speaker(s) 155, thewatermark will induce magnetic field variations at substantially thesame first range of frequencies in which the watermark was encoded.Accordingly, the watermark decoder 410 can evaluate the transformedmagnetic field data in the first range of frequencies to detect thewatermark.

In some examples, the watermark is added or otherwise included in theaudio signal in a first frequency range being below a threshold offrequencies capable of being emitted by the speaker(s) 155 (e.g., due tophysical limitations of the speaker diaphragm(s)). Because such a lowfrequency watermark (e.g., at or below 20-25 Hz) is not reproducible bythe speaker(s) 155, the low frequency watermark will not be detectablein the audio signal when emitted by the speaker(s) 155. However, such alow frequency watermark may still be detectable in the magnetic fielddata obtained from the magnetometer 145 (e.g., when the media devicemeter 125 is positioned within a first distance of the media device 110and/or the speaker(s) 155). Accordingly, watermark detection usingmagnetic field data as disclosed herein enables detection of audiowatermarks wirelessly but without relying on having access to the sourceaudio signal containing the watermark or a sensed acoustic signalcontaining the watermark.

The watermark detector 310 of FIG. 4 further includes an example aliascompensator 415 to compensate for the sampling frequency at which themagnetic field data is obtained by the magnetic field estimator 305 fromthe magnetometer 145. If the sampling frequency for obtaining themagnetic field data is less than twice a frequency component of thewatermark signal or, in other words, if the watermark frequencycomponent is greater than half the sampling frequency, then thatfrequency component of the watermark signal may experience aliasing. Insuch examples, the frequency component will be aliased and the effectsof that frequency component will appear at another frequency of thewatermark signal. For example, assume that the sampling frequency forobtaining the magnetic field data the magnetic field data is 41 Hz(e.g., which corresponds to the media metering device 125 being able toprovide 1230 magnetic field data samples in a 30 second interval). Ifthe watermark includes a first frequency component at 32 Hz, that firstfrequency component will be aliased due to the sampling at 41 Hz suchthat the energy at the component will appear at 9 Hz. As anotherexample, if the watermark includes a second frequency component at 45Hz, that second frequency component will be aliased due to the samplingat 41 Hz such that the energy at the component will appear at 4 Hz.Accordingly, the alias compensator 415 of the illustrated example usesthe sampling frequency for obtaining the magnetic field data todetermine whether to configure the watermark decoder 410 to compensatefor aliasing by evaluating the transformed magnetic field data at analiased frequency to detect a watermark at a different originalfrequency.

For example, if the watermark modulates a first frequency of the audiosignal, and the alias compensator 415 determines that the firstfrequency is greater than half the sampling rate, then the aliascompensator 415 selects a second frequency (e.g., based on a differencebetween the sampling rate and the first frequency), which is differentfrom the first frequency, at which the watermark decoder 410 is toevaluate the transformed magnetic field data to detect the watermark.The alias compensator 415 then configures the watermark decoder 410accordingly. Otherwise, if the first frequency is less than or equal tohalf the sampling rate, the alias compensator 415 does not perform aliascompensation and the watermark decoder 410 evaluates the transformedmagnetic field data at the first frequency to detect the watermark.

A second example implementation of the watermark detector 310 of FIG. 3is illustrated in FIG. 5 . The second example implementation is tailoredto detect watermarks encoded in one or more time domain characteristicsof the audio signal, such as by modulating the amplitude and/or phase ofthe audio signal in the time domain. Examples of watermarks encoded inthe time domain of an audio signal and that can be detected using theexample watermark detector 310 of FIG. 4 include, but are not limitedto, examples in which spread spectrum techniques are used to include awatermark in an audio signal. For example, such a watermark can beencoded in the audio signal by (1) spreading the watermark by modulatingthe watermark with a pseudo-noise sequence and then (2) combining thespread watermark with the audio signal. Detection of such a watermarkinvolves correlating the audio signal (after being watermarked) with thepseudo-noise sequence, which de-spreads the watermark, therebypermitting the watermark to be detected after the correlation.

Accordingly, the example watermark detector 310 of FIG. 5 includes anexample correlator 505 to correlate magnetic field data, such asmagnitude values determined by the magnitude field estimator 305 andrepresentative of a magnitude of a magnetic field over time, with areference sequence, such as a pseudo-noise sequence, to determine second(e.g., de-spread) magnetic field data. The example watermark detector310 of FIG. 5 also includes an example watermark decoder 510 to processthe second (e.g., de-spread) magnetic field data determined by thecorrelator 505 to detect the watermark. For example, the watermarkdecoder 510 may use any appropriate data decoding technique, such asmatched filter decoding, maximum likelihood decoding, etc., to detectthe watermark in the second (e.g., de-spread) magnetic field datadetermined by the correlator 505.

While example manners of implementing the media monitoring system 100are illustrated in FIGS. 1-5 , one or more of the elements, processesand/or devices illustrated in FIGS. 1-5 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example media device meter 125, the example network 135,the example data processing facility 140, the example magnetometer 145,the example media device monitor 150, the example magnetic fieldestimator 305, the example watermark detector 310, the example frequencytransformer 405, the example watermark decoder 410, the example aliascompensator 415, the example correlator 505, the example watermarkdecoder 510 and/or, more generally, the example media monitoring system100 of FIGS. 1-5 may be implemented by hardware, software, firmwareand/or any combination of hardware, software and/or firmware. Thus, forexample, any of the example media device meter 125, the example network135, the example data processing facility 140, the example magnetometer145, the example media device monitor 150, the example magnetic fieldestimator 305, the example watermark detector 310, the example frequencytransformer 405, the example watermark decoder 410, the example aliascompensator 415, the example correlator 505, the example watermarkdecoder 510 and/or, more generally, the example media monitoring system100 could be implemented by one or more analog or digital circuit(s),logic circuits, programmable processor(s), application specificintegrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s))and/or field programmable logic device(s) (FPLD(s)). When reading any ofthe apparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example mediamonitoring system 100, the example media device meter 125, the examplenetwork 135, the example data processing facility 140, the examplemagnetometer 145, the example media device monitor 150, the examplemagnetic field estimator 305, the example watermark detector 310, theexample frequency transformer 405, the example watermark decoder 410,the example alias compensator 415, the example correlator 505 and/or theexample watermark decoder 510 is/are hereby expressly defined to includea tangible computer readable storage device or storage disk such as amemory, a digital versatile disk (DVD), a compact disk (CD), a Blu-raydisk, etc. storing the software and/or firmware. Further still, theexample media monitoring system 100 of FIGS. 1-5 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 4 , and/or may include more than one of any or allof the illustrated elements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the example media monitoring system 100, the example mediadevice meter 125, the example network 135, the example data processingfacility 140, the example magnetometer 145, the example media devicemonitor 150, the example magnetic field estimator 305, the examplewatermark detector 310, the example frequency transformer 405, theexample watermark decoder 410, the example alias compensator 415, theexample correlator 505 and/or the example watermark decoder 510 areshown in FIGS. 6-8 . In these examples, the machine readableinstructions comprise one or more programs for execution by a processor,such as the processor 1112 shown in the example processor platform 1100discussed below in connection with FIG. 11 . The one or more programs,or portion(s) thereof, may be embodied in software stored on a tangiblecomputer readable storage medium such as a CD-ROM, a floppy disk, a harddrive, a digital versatile disk (DVD), a Blu-ray Disc™, or a memoryassociated with the processor 1112, but the entire program or programsand/or portions thereof could alternatively be executed by a deviceother than the processor 1112 and/or embodied in firmware or dedicatedhardware (e.g., implemented by an ASIC, a PLD, an FPLD, discrete logic,etc.). Also, one or more of the machine readable instructionsrepresented by the flowcharts of FIGS. 6-8 may be implemented manually.Further, although the example program(s) is(are) described withreference to the flowcharts illustrated in FIGS. 6-8 , many othermethods of implementing the example media monitoring system 100, theexample media device meter 125, the example network 135, the exampledata processing facility 140, the example magnetometer 145, the examplemedia device monitor 150, the example magnetic field estimator 305, theexample watermark detector 310, the example frequency transformer 405,the example watermark decoder 410, the example alias compensator 415,the example correlator 505 and/or the example watermark decoder 510 mayalternatively be used. For example, with reference to the flowchartsillustrated in FIGS. 6-8 , the order of execution of the blocks may bechanged, and/or some of the blocks described may be changed, eliminated,combined and/or subdivided into multiple blocks.

As mentioned above, the example processes of FIGS. 6-8 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example processes of FIGS. 6-8 may be implementedusing coded instructions (e.g., computer and/or machine readableinstructions) stored on a non-transitory computer and/or machinereadable medium such as a hard disk drive, a flash memory, a ROM, a CD,a DVD, a cache, a RAM and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media. As usedherein, when the phrase “at least” is used as the transition term in apreamble of a claim, it is open-ended in the same manner as the term“comprising” is open ended. Also, as used herein, the terms “computerreadable” and “machine readable” are considered equivalent unlessindicated otherwise.

An example program 600 that may be executed to implement the mediadevice meter 125 of FIGS. 1-5 is represented by the flowchart shown inFIG. 6 . With reference to the preceding figures and associated writtendescriptions, the example program 600 of FIG. 6 begins execution atblock 605 at which the media device meter 125 (e.g., which may be aportable device 125) is positioned within a first distance of the audiocircuitry that is to output an audio signal corresponding to media beingpresented by the media device 110. For example, and as described above,the media device meter 125 may be positioned within a first distance(e.g., adjacent to or within a few inches, feet or some other distance)of the media device 110 if the speaker(s) 155 are included in the mediadevice 110, or within the first distance of the speaker(s) 155, butfarther away from the media device 110, if the speaker(s) 155 areseparate from the media device 110 (e.g., as in the case of wirelessspeakers).

At block 610, the magnetic field estimator 305 of the media device meter125 (e.g., which is included in the media device monitor 150 of themedia device meter 125) accesses magnetic field data obtained from themagnetometer 145 of the media device meter 125, as described above. Atblock 615, the magnetic field estimator 305 processes the magnetic fielddata obtained at block 610 to estimate magnitude values of the magneticfield value (e.g., using Equation 3 or 4), as described above. At block620, the watermark detector 310 of the media device meter 125 (e.g.,which is included in the media device monitor 150 of the media devicemeter 125) processes the magnetic field magnitude values determined atblock 615 to detect a watermark that was induced in the magnetic fielddata by the audio signal provided to the speaker(s) 155 of the mediadevice 110, as described above. Example machine readable instructionsthat may be used to implement the processing at block 620 areillustrated in FIGS. 7 and 8 , which are described in further detailbelow.

At block 625, the media device monitor 150 of the media device meter 125stores the detected watermark data and reports the detected watermarkdata to the data processing facility 140 for further processing. Ifwatermark detection processing is to continue (block 630), processingreturns to block 610 and blocks subsequent thereto to permit the mediadevice meter 125 to continue detecting watermarks using magnetic fielddata. Otherwise, execution of the example program 600 ends.

An example program 620P1 that may be executed to implement the examplewatermark detector 310 of FIGS. 3 and/or 4 , and/or that may be used toimplement the processing at block 620 of FIG. 6 , is represented by theflowchart shown in FIG. 7 . With reference to the preceding figures andassociated written descriptions, the example program 620P1 of FIG. 7begins execution at block 705 at which the frequency transformer 405 ofthe watermark detector 310 transforms magnetic field magnitude values(e.g., obtained from the magnitude field estimator 305) to a frequencydomain to determine transformed magnetic field data, as described above.At block 710, the alias compensator 415 of the watermark detector 310determines whether frequency component(s) of the watermark(s) to bedetected are located at frequencies greater than half the sampling rateat which the magnetic field data is accessed (e.g., by the magnitudefield estimator 305). If the frequency component(s) of the watermark(s)are greater than half the magnetic field data sampling rate (block 710),processing proceeds to block 715 at which the alias compensator 415selects one or more aliased frequencies at which the watermark decoder410 of the watermark detector 310 is to evaluate the transformedmagnetic field data to detect the watermark(s), as described above.After processing at block 715 completes, or if the frequencycomponent(s) of the watermark(s) are not greater than half the magneticfield data sampling rate (block 710), processing proceeds to block 720at which the watermark detector 310 evaluates the transformed magneticfield data to detect the watermark(s), as described above. For example,at block 720 the watermark detector 310 evaluates the transformedmagnetic field data at the original frequency or frequencies of thewatermark(s) if the original frequency component(s) of the watermark(s)are not greater than half the magnetic field data sampling rate, and/orevaluates the transformed magnetic field data at the aliased frequencyor frequencies of the watermark(s) if the original frequencycomponent(s) of the watermark(s) are greater than half the magneticfield data sampling rate. Execution of the example program 620P1 thenends.

An example program 620P2 that may be executed to implement the examplewatermark detector 310 of FIGS. 3 and/or 5 , and/or that may be used toimplement the processing at block 620 of FIG. 6 , is represented by theflowchart shown in FIG. 8 . With reference to the preceding figures andassociated written descriptions, the example program 620P2 of FIG. 8begins execution at block 805 at which the correlator 505 of thewatermark detector 310 correlates magnetic field data, such as magnitudevalues determined by the magnitude field estimator 305 andrepresentative of a magnitude of a magnetic field over time, with areference sequence, such as a pseudo-noise sequence, to determine second(e.g., de-spread) magnetic field data, as described above. At block 810,the watermark decoder 510 of the watermark detector 310 processes thesecond (e.g., de-spread) magnetic field data determined at block 805 todetect the watermark(s), as described above. Execution of the exampleprogram 620P2 then ends.

FIGS. 9-10 illustrate example operational results that can be achievedby the example media device monitor 150 of FIGS. 1-3 when detecting awatermark in magnetic field data. In the illustrated examples of FIGS.9-10 , a watermark is embedded as a single frequency tone in the audiosignal. In the example of FIG. 9 , the watermark is embedded as a 32 Hztone, whereas in the example of FIG. 10 , the watermark is embedded as a45 Hz tone. In the illustrated examples, the sampling frequency forobtaining the magnetic field data the magnetic field data is 41 Hz, andthe media device monitor 150 processes 1230 magnetic field magnitudevalues determined over a 30 second period to detect watermark. Thegraphs in FIGS. 9 and 10 depict example results for detecting therespective watermarks embedded at the respective frequencies of 32 Hzand 45 Hz. In FIGS. 9 and 10 , the x-axis corresponds to a frequencyindex, which can be converted to an actual frequency by multiplying thefrequency index by the sampling frequency (41 Hz) and dividing by thetotal number of samples (1230) being processed. In the example of FIG. 9, it can be seen that the media device monitor 150 is able to detect thewatermark embedded at 32 Hz as a peak at approximately 9 Hz due toaliasing (i.e., the peak at frequency index 266 corresponds to a peak at266×41/1230=8.9 Hz). Similarly, in the example of FIG. 10 , it can beseen that the media device monitor 150 is able to detect the watermarkembedded at 45 Hz as a peak at approximately 4 Hz due to aliasing (i.e.,the peak at frequency index 118 corresponds to a peak at 118×41/1230=3.7Hz).

FIG. 11 is a block diagram of an example processor platform 1100 capableof executing the instructions of FIGS. 6-8 to implement the examplemedia monitoring system 100, the example media device meter 125, theexample network 135, the example data processing facility 140, theexample magnetometer 145, the example media device monitor 150, theexample magnetic field estimator 305, the example watermark detector310, the example frequency transformer 405, the example watermarkdecoder 410, the example alias compensator 415, the example correlator505 and/or the example watermark decoder 510 of FIGS. 1-5 . Theprocessor platform 1100 can be, for example, a server, a personalcomputer, a mobile device (e.g., a cell phone, a smart phone, a tabletsuch as an iPad®), a personal digital assistant (PDA), an Internetappliance, a DVD player, a CD player, a digital video recorder, aBlu-ray player, a gaming console, a personal video recorder, a set topbox a digital camera, or any other type of computing device.

The processor platform 1100 of the illustrated example includes aprocessor 1112. The processor 1112 of the illustrated example ishardware. For example, the processor 1112 can be implemented by one ormore integrated circuits, logic circuits, microprocessors or controllersfrom any desired family or manufacturer.

The processor 1112 of the illustrated example includes a local memory1113 (e.g., a cache) (e.g., a cache). The processor 1112 of theillustrated example is in communication with a main memory including avolatile memory 1114 and a non-volatile memory 1116 via a link 1118. Thelink 1118 may be implemented by a bus, one or more point-to-pointconnections, etc., or a combination thereof. The volatile memory 1114may be implemented by Synchronous Dynamic Random Access Memory (SDRAM),Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory(RDRAM) and/or any other type of random access memory device. Thenon-volatile memory 1116 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 1114,1116 is controlled by a memory controller.

The processor platform 1100 of the illustrated example also includes aninterface circuit 1120. The interface circuit 1120 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 1122 are connectedto the interface circuit 1120. The input device(s) 1122 permit(s) a userto enter data and commands into the processor 1112. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, a trackbar (such as an isopoint), a voicerecognition system and/or any other human-machine interface.

One or more output devices 1124 are also connected to the interfacecircuit 1120 of the illustrated example. The output devices 1124 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a light emitting diode (LED), a printer and/or speakers).The interface circuit 1120 of the illustrated example, thus, typicallyincludes a graphics driver card, a graphics driver chip or a graphicsdriver processor.

The interface circuit 1120 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network1126 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 1100 of the illustrated example also includes oneor more mass storage devices 1128 for storing software and/or data.Examples of such mass storage devices 1128 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAID(redundant array of independent disks) systems, and digital versatiledisk (DVD) drives.

Coded instructions 1132 corresponding to the instructions of FIGS. 6-8may be stored in the mass storage device 1128, in the volatile memory1114, in the non-volatile memory 1116, in the local memory 1113 and/oron a removable tangible computer readable storage medium, such as a CDor DVD 1136.

From the foregoing, it will be appreciated that methods, apparatus,systems and articles of manufacture (e.g., physical storage media) todetect media watermarks in magnetic field data have been disclosed.Practical applications of watermark detection using magnetic field data,as disclosed herein, include, but are not limited to, contentrecognition, source detection, security applications, etc. For example,content recognition can performed using a portable device as disclosedherein and positioned near the speakers of a media device. In the caseof source detection, the media device (e.g., a set top box, DVD player,game console, etc.) can add a low-frequency watermark to the audiosignal on-the-fly, which can be detected as disclosed herein and used toidentify the source of the media being presented. In some securityapplications, the watermarks can provide a secure channel ofcommunication that can be used to perform user authentication, deviceauthentication, etc.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. A media monitor comprising: a magnetic fieldestimator to determine first magnetic field data, the magnetic fieldestimator in communication with a magnetometer; a correlator tocorrelate the first magnitude field data with a reference sequence todetermine second magnetic field data; and a watermark decoder to processthe second magnetic field data to detect an audio watermark encoded inan audio signal.
 2. The media monitor of claim 1, further including anoutput indicator to be asserted when the watermark decoder detects theaudio watermark.
 3. The media monitor of claim 1, wherein the magneticfield estimator is in communication with the magnetometer via anapplication programming interface of a media device.
 4. The mediamonitor of claim 1, wherein the audio signal is output by audiocircuitry of a media device, the audio circuitry includes speaker leadsto electrically couple a speaker driver circuit to a speaker that is toreproduce the audio signal, and the magnetic field estimator is toprocess the second magnetic field data to detect variations in thesecond magnetic field that are induced by an electrical signal carriedby the speaker leads.
 5. The media monitor of claim 1, wherein thereference sequence is a pseudo-noise sequence.
 6. The media monitor ofclaim 5, wherein the audio signal is a first audio signal, and the audiowatermark is encoded in the first audio signal by: modulating the audiowatermark with the pseudo-noise sequence to determine a modulated audiowatermark; and combining the modulated audio watermark with a secondaudio signal to produce the first audio signal.
 7. The media monitor ofclaim 1, wherein the watermark decoder is to process the second magneticfield data with a matched filter to detect the audio watermark.
 8. Themedia monitor of claim 1, wherein the first magnetic field data isrepresentative of a magnitude of a magnetic field measured by themagnetometer over time.
 9. A non-transitory computer readable mediumcomprising computer readable instructions that, when executed, cause aprocessor to at least: determine first magnetic field datarepresentative of a magnitude of a magnetic field measured by amagnetometer over time; correlate the first magnitude field data with areference sequence to determine second magnetic field data; and processthe second magnetic field data to detect an audio watermark encoded inan audio signal.
 10. The non-transitory computer readable medium ofclaim 9, wherein the instructions cause the processor to assert anoutput indicator when the audio watermark is detected.
 11. Thenon-transitory computer readable medium of claim 9, wherein theinstructions cause the processor to access the magnetometer via anapplication programming interface.
 12. The non-transitory computerreadable medium of claim 9, wherein the audio signal is output by audiocircuitry of a media device, the audio circuitry includes speaker leadsto electrically couple a speaker driver circuit to a speaker that is toreproduce the audio signal, and the instructions cause the processor toprocess the second magnetic field data to detect variations in thesecond magnetic field that are induced by an electrical current carriedby the speaker leads.
 13. The non-transitory computer readable medium ofclaim 9, wherein the reference sequence is a pseudo-noise sequence. 14.The non-transitory computer readable medium of claim 13, wherein theaudio signal is a first audio signal, and the audio watermark is encodedin the first audio signal by: modulating the audio watermark with thepseudo-noise sequence to determine a modulated audio watermark; andcombining the modulated audio watermark with a second audio signal toproduce the first audio signal.
 15. A media monitoring methodcomprising: determining, by executing an instruction with a processor,first magnetic field data representative of a magnitude of a magneticfield measured by a magnetometer over time; correlating, by executing aninstruction with the processor, the first magnitude field data with areference sequence to determine second magnetic field data; andprocessing, by executing an instruction with the processor, the secondmagnetic field data to detect an audio watermark encoded in an audiosignal.
 16. The media monitoring method of claim 15, further includingasserting an output indicator when the audio watermark is detected. 17.The media monitoring method of claim 15, further including accessing themagnetometer via an application programming interface.
 18. The mediamonitoring method of claim 15, wherein the audio signal is output byaudio circuitry of a media device, the audio circuitry includes speakerleads to electrically couple a speaker driver circuit to a speaker thatis to reproduce the audio signal, and the processing of the secondmagnetic field data includes processing the second magnetic field datato detect variations in the second magnetic field that are induced by anelectrical current carried by the speaker leads.
 19. The mediamonitoring method of claim 15, wherein the reference sequence is apseudo-noise sequence.
 20. The media monitoring method of claim 19,wherein the audio signal is a first audio signal, and the audiowatermark is encoded in the first audio signal by: modulating the audiowatermark with the pseudo-noise sequence to determine a modulated audiowatermark; and combining the modulated audio watermark with a secondaudio signal to produce the first audio signal.